Groq vs Qwen 2.5
- ✦ Ultra-Fast Inference
- ✦ Llama 3 Models
- ✦ Mixtral Models
- ✦ Open Source Weights
- ✦ Multilingual (29+ languages)
- ✦ Code Generation
Groq and Qwen 2.5 are both Large Language Models tools. Compare features, pricing, and ratings below to find the best fit for your team.
When to Choose Groq vs Qwen 2.5
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Groq's LPU delivers Llama 3 inference at 750+ tokens per second, enabling pipelines where Whisper transcription feeds directly into an LLM analysis step with a total round-trip under 500ms.
Groq's time-to-first-token under 100ms enables natural-feeling voice conversational interfaces where LLM response latency is the bottleneck, not TTS or ASR.
Groq's per-token cost on Llama 3 8B is under $0.06 per million tokens, making high-volume classification or extraction tasks that previously required GPU servers economically viable via API.
Qwen 2.5's 128K context window processes multilingual contracts or reports and translates, summarizes, or extracts structured data in 29 languages with stronger CJK performance than most non-Chinese LLMs.
Qwen 2.5-Coder outperforms same-parameter models on HumanEval benchmarks, generating Python, TypeScript, and Rust code that compiles correctly at a higher rate per token budget.
Qwen 2.5's 128K context processes an entire technical manual in a single call, reducing the chunk-and-retrieve complexity for document QA applications that fail when context spans multiple chunks.
Pricing Comparison & PlansHigh· Verified May 30, 2026
Groq Plans
Free tier available
Free
FreeBest for: 14,400 req/day is enough for dev and low-traffic apps - start here before paying anything.
- ✓Build and Test on Groq APIs
- ✓Community Support
- ✓Zero-data Retention Available
Developer
Contact Sales- ✓Build and Test on Groq APIs
- ✓Community Support
- ✓Zero-data Retention Available
- ✓Higher Token Limits
- ✓Chat Support
Enterprise
Contact Sales- ✓Build and Test on Groq APIs
- ✓Community Support
- ✓Zero-data Retention Available
- ✓Higher Token Limits
- ✓Chat Support
Qwen 2.5 Plans
Free tier available
Open Source
Open Source- ✓Free model weights download
- ✓Permissive commercial licensing
- ✓Self-hostable on local or cloud infrastructure
- ✓Access to multiple model sizes (0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B)
- ✓Supports up to 128K context length
API (Alibaba Cloud DashScope)
Contact Sales- ✓Pay-as-you-go pricing per million tokens
- ✓Free tier token quota for new users
- ✓Fully managed API with high concurrency
- ✓OpenAI-compatible API integration
- ✓Access to specialized Coder and Math models
Capability Breakdown
5 differences found across 15 standardized features
- •Ultra-Fast Inference
- •Llama 3 Models
- •Mixtral Models
- •Gemma Models
- •OpenAI-Compatible API
- •Function Calling
- •JSON Mode
- •Streaming
- •Tool Use
- •Low Latency
- •High Throughput
- •Free Tier
- •Python SDK
- •JavaScript SDK
- •LPU Hardware
- •Open Source Weights
- •Multilingual (29+ languages)
- •Code Generation
- •Math Reasoning
- •Long Context (128k)
- •Function Calling
- •JSON Mode
- •Fine-tuning Support
- •GGUF Format
- •Ollama Support
- •vLLM Support
- •Instruction Following
- •System Prompts
- •Commercial License
- •Multiple Sizes
- •REST API
- •Streaming API
- •SDK (Python, JS)
- •Batch Processing
Strengths & Limitations
Evaluative strengths and weaknesses: not feature lists
- +World's fastest inference speed (500+ tokens/sec)
- +Custom LPU hardware eliminates sequential processing bottlenecks
- +OpenAI-compatible API for seamless, drop-in integration
- +Predictable, low-latency performance regardless of load
- +Generous free tier for development and testing
- −Very limited selection of open-source models (no GPT-4, Claude)
- −No support for fine-tuning or custom model hosting
- −Lacks advanced features like function calling or JSON mode on some models
- −Rate limits can be a bottleneck for high-throughput applications
- −Newer hardware, less proven for enterprise-scale reliability
- +Fully open source with commercial license
- +Top-tier performance among open models
- +Excellent multilingual capabilities
- +Strong coding and math benchmarks
- −Requires GPU for self-hosting larger models
- −Less polished tooling than OpenAI
- −API primarily through Alibaba Cloud
At a Glance
Recent Price History
Groq added a new "Developer" plan (Custom pricing)
Plan added · May 30, 2026
Groq removed the "Pay-as-you-go" plan
Plan removed · May 30, 2026
Groq added a new "Enterprise" plan
Plan added · May 21, 2026
Qwen 2.5 removed the "API (Alibaba Cloud)" plan
Plan removed · May 21, 2026
Qwen 2.5 added a new "API (Alibaba Cloud DashScope)" plan
Plan added · May 21, 2026
Frequently Asked Questions
Related Comparisons
Sources & Data Trail · Groq
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-05-30)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4.7/5 · 915 reviews
- 4.PeerSpot·PeerSpot enterprise peer reviews
Sources & Data Trail · Qwen 2.5
- 1.Official Pricing Page·Source of verified tiers(Checked: 2026-05-14)
- 2.Official Website·Official vendor website
- 3.G2·G2 verified reviews · 4.4/5 · 31,279 reviews